Detailed Resume | Education | Supervision | Editorial |
Dr. Hammad Afzal is an accomplished academician, currently working as a Professor and Scientific Director of “AI Research Lab – A Collaborative Organization for Data-driven AI Technologies and Emerging Engineering Methods (CODTEEM)” at the National University of Sciences and Technology, Pakistan. He is recognized for his contributions in the fields of machine learning (ML), natural language processing (NLP), and applied ML in cutting-edge domains, including smart healthcare, multi-lingual NLP, and information security. In Multi-lingual NLP, he is positioned among the top 10% of most cited researchers on Google Scholar.
Dr. Hammad completed PhD in Computer Science from the School of Computer Science, University of Manchester, UK and worked as a Research Intern at Insight Center for Data Analytics, University of Ireland, Galway. He did an MSc in Advanced Computing Sciences from the University of Manchester, UK where he was awarded the Program Prize of the Year from the Department of Computation for acquiring the highest grades in MS courses. He has also garnered professional training and certifications from prestigious institutes such as IBM, DeepLearning.AI, Microsoft, and Google.
He has over 15 years of teaching and research experience at various educational and research institutions. He has over 100 publications (with a Cumulative Impact Factor of 227) in highly prestigious refereed international journals and conferences. He has supervised 3 PhD and 63 MS students. He is currently engaged in various funded projects, supported by a substantial funding amount of more than 20 Million PKR from various resources including Research and Academic Collaboration, Govt of Pakistan, National Grassroots ICT Research Initiative, and BBSRC-funded project (UK).
Dr. Hammad is a professional member of various national and international bodies such as IEEE (Senior Member) ACM, and Pakistan Engineering Council (PEC). He has served as the Head of UG Curriculum Committee, PEC, and HEC, for Sub-Group Software Engineering. He has also served as an evaluator for several National R&D programs including ICT R&D, NGIRI, NTS etc. He has also attained several awards such as Best Researcher MCS NUST of the year 2019, and Peter Jones Prize of the year 2005, to attain highest grades in all MSc courses in the Department of Informatics, University of Manchester, UK (Equivalent to Gold Medal).
He has contributed extensively to the academic community by serving as Chair, Co-Chair and a member of the Technical Program Committee for several conferences, e.g. WETICE, ICMMI, ICOSST, MedPRAI etc. He has served as a reviewer of over 20 reputed international journals including IEEE Communications Magazines, the Journal of Natural Language Engineering, Neural Computing and Applications, Cluster Computing, etc. Apart from that, currently, he holds the position of Associate Editor for Human-centric Computing and Information Sciences, (a journal ranked in Q1 and in the top 10% according to Scopus and WoS) as well as for Mobile Information Systems. Additionally, he has had the honor of serving as a Guest Editor for two special issues in Security and Communication Networks (ranked in Q2 according to Scopus).
Roles
- Professor (NUST)
- Head of Research (MCS-NUST)
- PG Program Coordinator (Dept of Computer Software Engg, NUST)
- Lead Sub-Group Software Engineering ECRDC, Pakistan Engineering Council (Curriculum 2020)
- Member ACM | Senior Member IEEE | PEC Recognized Engr | HEC Approved Supervisor;
Education
- PhD Computer Science, University of Manchester, UK (2009)
Thesis: A Literature-Based Framework for Semantic Descriptions of e-Science Resources - MSc Computer Science, University of Manchester, UK [Distinction] (2005)
Thesis: Topic Focused Web Crawler
Honour: Peter Jones Prize for the highest score among all MSc students in the Department of Informatics - BE Software Engg, National University of Sciences and Technology, Pakistan (2003)
CGPA: 3.53/4.0 (Honours) - Google Cloud – Coursera
Google Cloud Big Data and Machine Learning Fundamentals
Google Cloud Fundamentals: Core Infrastructure - DeepLearning.AI – Coursera
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
Neural Networks and Deep Learning – DeepLearning.AI – Coursera
Effective Problem-Solving and Decision-Making -University of California, Irvine – Coursera
Supervision
PhD Students Graduated
1. Sabeen Javaid: A Web of Things Architecture Focusing on Trust
- Graduation Date: 5 Sep 2019
- Publication: CATSWoTS: Context Aware Trustworthy Social Web of Things System
- Publication: ARCA-IoT: An Attack-Resilient Cloud-Assisted IoT System
- Publication: Trust management for SOA based social WoT system
- Publication: Reputation Management System for Fostering Trust in Collaborative and Cohesive Disaster Management
2. Zeeshan Anwar: Mining Crowdsourcing Repositories for Open Innovation in Software Engineering
- Graduation Date: 7 Jun 2024
- Publication: Fuzzy ensemble of fined tuned BERT models for domain-specific sentiment analysis of software engineering dataset
- Publication: Mining the Opinions of Software Developers for Improved Project Insights: Harnessing the Power of Transfer Learning
- Publication: Mining crowd-sourcing repositories for open innovation in software engineering
- Publication: Collaborative Solutions to Software Architecture Challenges Faced by IT Professionals
- Publication: A novel hybrid CNN-LSTM approach for assessing StackOverflow post quality
3. Naureen Zainab Temporal Detection and Classification of Citrus Canker Growth Rate
- Graduation Date: 16 Feb 2024
- Publication: Detection and Classification of Temporal Changes for Citrus Canker Growth Rate Using Deep Learning
- Publication: Diagnosis and Identification of Citrus Canker Growth Rate Using Machine Learning
PhD Students Current
1. Muhammad Waheed Khan: Multiclass Vulnerabilities Discovery and Severity Analysis in Mobile Platforms
2. Sumair Shaukat: Text-to-Image Synthesis of Medical Images using Diffusion Modeling
3. Quratulain: Classification of Severity Level of Dysarthria Disease and Voice Reconstruction using Deep Learning
4. Mobina Zafar: Exploring Large Language Models for Story generation for low resource languages.
MSc Students Graduated
Teaching
I have been regularly teaching one/two courses each semester. My Teaching schedule has been like below:
Spring, 2024 | Data Warehousing and Data Mining | Undergraduate |
Fall, 2023 | Machine Learning | Undergraduate |
Summer, 2023 | Data Structures and Algorithms | Undergraduate |
Spring, 2023 | Machine Learning | Postgraduate |
Fall, 2022 | Machine Learning | Undergraduate |
Spring, 2022 | Deep Learning | Postgraduate |
Spring, 2022 | Data Warehousing and Data Mining | Undergraduate |
Fall, 2021 | Machine Learning | Undergraduate |
Fall, 2021 | Machine Learning | Undergraduate |
Spring, 2021 | Data Warehousing and Data Mining | Undergraduate |
Spring, 2021 | Machine Learning | Postgraduate |
Fall, 2020 | Data Warehousing and Data Mining | Undergraduate |
Fall, 2020 | Data Warehousing and Data Mining | Undergraduate |
Spring, 2020 | Data Warehousing and Data Mining | Undergraduate |
Spring, 2020 | Machine Learning | Postgraduate |
Fall, 2019 | Computer Organization and Architecture | Undergraduate |
Fall, 2019 | Machine Learning | Postgraduate |
Spring, 2019 | Data Warehousing and Data Mining | Undergraduate |
Spring, 2019 | Machine Learning | Undergraduate |
Summer, 2018 | Object Oriented Programming | Undergraduate |
Spring, 2018 | Machine Learning | Postgraduate |
Spring, 2018 | Object Oriented Programming | Undergraduate |
Fall, 2017 | Data Mining and Warehousing | Undergraduate |
Spring, 2017 | Object Oriented Programming | Undergraduate |
Spring, 2017 | Machine Learning | Postgraduate |
Fall, 2016 | Data Mining and Warehousing | Undergraduate |
Spring, 2016 | Computer Organization and Architecture | Undergraduate |
Spring, 2016 | Machine Learning | Postgraduate |
Fall, 2015 | Data Mining and Warehousing | Undergraduate |
Summer, 2015 | Machine Learning | Postgraduate |
Spring, 2015 | Software Quality Engineering | Postgraduate |
Fall, 2014 | Data Mining and Warehousing | Undergraduate |
Summer, 2014 | Object Oriented Programming | Undergraduate |
Spring, 2014 | Distributed Computing | Undergraduate |
Spring, 2014 | Advanced Databases | Postgraduate |
Fall, 2013 | Object Oriented Programming | Undergraduate |
Spring, 2013 | Data Mining | Undergraduate |
Spring, 2013 | Computer Org and Arch | Undergraduate |
Fall 2012 | Operating Systems | Undergraduate |